Cloud Data Production Support Engineer

At Schwab, you’re empowered to make an impact on your career. Here, innovative thought meets creative problem solving, helping us challenge the status quo and transform the finance industry together. We believe in the importance of in-office collaboration and fully intend for the selected candidate for this role to work on site in the specified location(s).

Schwab Technology Services enables the future of how clients manage their money by delivering innovative, scalable, and reliable technology solutions that support investing and financial planning. Within this environment, the Data Engineering team plays a critical role in advancing enterprise data and analytics capabilities that power informed decision-making across the firm.

As a Cloud Data Engineer focused on production support operations, you will lead and contribute to the reliability, scalability, and performance of enterprise data platforms in a cloud-based ecosystem. You will partner closely with data engineering, platform, and business teams to ensure data pipelines, workflows, and services operate consistently and meet service expectations. In this role, you will help strengthen operational excellence by improving monitoring, automation, and incident response practices while supporting large-scale, high-availability data environments.

You will leverage your experience across cloud technologies, data pipelines, and observability frameworks to enhance system reliability and data availability. This role offers the opportunity to drive continuous improvement, support complex data workloads, and contribute to a collaborative environment where diverse perspectives and ideas are valued.

• 7+ years of experience in production support, operations, or reliability roles within data analytics, data engineering, or data warehouse environments
• 4+ years of experience supporting Informatica Data Management Cloud (IDMC) in production environments
• Proven experience supporting enterprise-scale data platforms with high availability and reliability requirements
• Strong hands-on experience with cloud-based data platforms and services, including GCP BigQuery, Cloud Composer (Airflow), Dataflow, and Pub/Sub
• Experience supporting ETL and data pipeline workloads (IDMC or equivalent) in production environments
• Experience with orchestration frameworks, including DAG-based workflows, streaming pipelines, and event-driven processing
• Strong understanding of GCS concepts, including file ingestion, partitioning, lifecycle management, and data availability tracking
• Strong SQL skills for data analysis, validation, and troubleshooting
• Experience using Python or scripting languages for automation and operational improvements
• Experience working with APIs, SDKs, or CLI tools (e.g., GCP SDK, REST APIs) for automation and monitoring integration
• Experience with observability and monitoring tools such as Grafana, Prometheus, or equivalent
• Ability to design and implement monitoring dashboards aligned to service level objectives (SLO/SLA), pipeline health, and data availability
• Experience with job scheduling and orchestration tools such as Control-M or Cloud Composer
• Experience with CI/CD tools such as GitHub and deployment workflows
• Strong understanding of monitoring, alerting, and incident management practices in production systems
• Experience building observability solutions across batch and streaming data pipelines
• Experience driving automation initiatives to improve operational efficiency and reduce manual effort
• Experience working with large-scale, complex data platforms with high data volume and interdependent pipelines

• Experience working in financial services or regulated environments, including data governance and operational controls

In addition to the salary range, this role is also eligible for bonus or incentive opportunities.